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April 21, 2026

Identification of Drug-resistant Cell Subpopulations in Colorectal Cancer Through Single-cell Analysis and Exploration of Potential Therapeutic Strategies

Key Points

This study aims to identify drug-resistant cell subpopulations in colorectal cancer and explore therapeutic strategies.
Utilized single-cell RNA sequencing data from GEO database for analysis.
Identified differentially expressed genes between resistant and sensitive epithelial cell subpopulations.
Conducted enrichment analysis and validated findings with external datasets.
Identified 10 cell clusters, with EpC2 representing a significant oxaliplatin-resistant subpopulation.
Enriched pathways included TNF and IL-17, indicating multi-layered resistance mechanisms.
Dasatinib was predicted as a potential therapeutic candidate for overcoming resistance.

Abstract

Introduction: The therapeutic efficacy of Colorectal Cancer (CRC) is often compromised by resistance to the standard chemotherapy agent oxaliplatin. Methods: This study obtained single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Differentially Expressed Genes (DEGs) between resistant and sensitive epithelial subpopulations were identified, followed by enrichment analysis. Pseudotemporal trajectory and cell-cell communication were analyzed using Monocle2 and CellChat, respectively. The candidate drug was predicted by Connectivity Map (cMAP) analysis. External validation included assessment of the EpC2 signature in an oxaliplatin-resistant cell line dataset (GSE76092), survival analysis using The Cancer Genome Atlas (TCGA) cohorts, and re-analysis of the GSE179784 dataset to assess the reproducibility of EpC2-like subpopulations and their DNA Damage Repair (DDR) scores. Results: Cell subpopulations were divided into 10 clusters. Among them, epithelial cells comprised 5 subpopulations, with EPC2 identified as a potential oxaliplatin-resistant subset. DEGs were enriched in the TNF and IL-17 pathways. External validation confirmed the enrichment of EpC2 in resistant cell lines and its association with poor survival. Pseudotemporal trajectory revealed that epithelial cells underwent state transitions, forming two distinct branches. The resistant group exhibited enrichment in RNA splicing and NF-κB pathways. Cell-cell communication analysis revealed interactions involving MDK- NCL and PPIA-BSG. Dasatinib was predicted as a candidate drug. Discussion: We identified an oxaliplatin-resistant subpopulation of Epithelial Cells (EpC2) in CRC, elucidated its multi-layered resistance mechanisms, and integrated multi- omics and cMAP database analyses to predict a potential intervention drug. conclusion: This study offers potential therapeutic possibilities for oxaliplatin resistance and provides more clues for clinical treatment of CRC. Conclusion: This study provided potential therapeutic possibilities for oxaliplatin resistance, contributing to CRC treatment.

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